What do the words "coarse" and "fine" mean in the context of computer vision?
tl;dr


  What does that mean in the context of this paper?


With "coarse segmentation" the author means a segmentation that doesn't have much detail. "Fine segmentation", on the other hand, refers to a segmentation with a high level of detail.


  But also more importantly [what does that mean in the context of] general computer vision?


The most common use in CV is to describe how general or specific a class in is classification. A "coarse class" is a very broad one, while a "fine class" is a very specific one.

Intended use

What the author refers to is the level of detail of the resulting segmentation. 

A coarse segmentation would mean that we have large blobs covering each class without much detail. On the other hand, a fine segmentation would have a much higher level of detail which can even go down to pixel level (i.e. pixel-by-pixel correct segmentation).

To make this clear look at the following two examples. As we go from the left to right, the segmentation maps go from coarse to fine:




Note that in the rightmost images the result an almost pixel-perfect (i.e. fine details) segmentation map, while the ones on the left don't have much detail and can be considered coarse.

Alternative use

Because this isn't an established terminology, some of the times coarse and fine can refer to the nature of the classes in a classification task. Take the top image for example; the label for a coarse classification task could be a tree. For a fine classification task we would have labels like oak tree, pine tree, etc. 

The most prominent example of this is the cifar dataset which has two versions: a coarse one that has 10 classes and a fine one that has 100 classes, which are all subclasses of the coarse classes. For example a coarse class is fish, while the fine ones are aquarium fish, flatfish, ray, shark, trout, etc.

For semantic segmentation an example could be the following: you want to make a street segmentation model. This a coarse segmentation would mean that it just splits the image into road, vehicle, etc. A fine segmentation, on the other hand, could also detect the type of vehicle, e.g. truck, car, etc.